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Large-scale discovery of potent, compact and lineage specific enhancers for gene therapy vectors [RNA-seq]

GSE252161 Homo sapiens (human) RNA-seq (gene expression) 16 samples Submitted 2024/05/01 Platform GPL20301Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 16 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Samples
16 samples: 5 × TL17276 & TL17287:TL17288 transfected, clone 24, vs 5 × HUDEP-2 mock transfected, clone 36, vs 3 × HUDEP-2 mock transfected, clone 62 vs 3 × TL20805 transfected, clone 124,Groups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Summary (written by the submitters)
Regulation of gene expression during cell development and differentiation is chiefly orchestrated by distal noncoding regulatory elements that precisely modulate cell selective gene activity. Gene therapy vectors rely on the cellular and context specificity of regulatory DNA elements to express therapeutic transgenes in the correct location and time.
Read the full summary ↓
Here, we develop a straight-forward, one-shot approach to screen putative regulatory sequences identified in large-scale epigenomics profiling experiments for precise and programmable control of transgenes encoded within gene therapy viral vectors. We designed a library of 15,000 short sequences (~200bp) derived from a set of developmentally active DHS elements during human ex vivo erythropoiesis and cloned them into a GFP reporter lentiviral vector. In an erythroid progenitor cell line, these elements display a gradient of transcriptional enhancer activity, with some demonstrating equivalent activity to the canonical β-globin μLCR despite a 9-fold smaller size. We show that these elements are both highly cell type restricted and developmental stage specific both in vitro and in vivo. Finally, we replace the μLCR element with one of the novel short enhancers in a β-thalassemia lentiviral therapeutic vector and efficiently correct the thalassemic phenotype in patient-derived HSPCs. More broadly, our approach provides further insights into enhancer biology with wider implications into the development of highly cell type specific and efficacious viral vectors for human gene therapy.
This dataset
Open GSE252161 in finder → Find more human RNA-seq datasets →
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE252161_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1057939 and SRA study SRP480341. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
5 × TL17276 & TL17287:TL17288 transfected, clone 24, vs 5 × HUDEP-2 mock transfected, clone 36, vs 3 × HUDEP-2 mock transfected, clone 62 vs 3 × TL20805 transfected, clone 124,

Supports a between-group comparison across 16 samples.

How we read this: 4 replicated groups read from 16 sample titles; they account for 16 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study
Datasets on a similar topic

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